# Decoding glioma evolution and progression by multi-dimensional single-cell profiling > **NIH NIH R00** · UNIVERSITY OF PENNSYLVANIA · 2024 · $249,000 ## Abstract PROJECT SUMMARY / ABSTRACT Research Plan: Tumor evolution is a fundamental obstacle to cancer treatment, as malignant cells adapt to treatment and change during progression. Understanding these adaptations is key to not only identifying vulnerable gene targets, but also intervening during the optimal time window, before the targets become obsolete. Charting this evolution requires understanding the genetic and epigenetic events that drive or accompany disease progression, but these are largely unmapped in many malignancies. A case in point is diffuse glioma, an incurable brain cancer composed of distinct cellular states that dramatically change in relative abundance during glioma progression, ultimately changing the response to treatment. Efforts to decode glioma evolution have been limited: while we have characterized the distinct glioma cell states, we have not found their genetic and epigenetic drivers or measured how these affect cell states abundance throughout progression. To this end, we have developed novel single-cell technologies to concurrently profile in the same cell i) the transcriptome and epigenome (specifically, DNA methylation) and ii) the transcriptome and genome (DNA mutations) at an unprecedented detection rate. First, by combining genotype with cellular state data, I will define how somatic mutations dysregulate transcriptional patterns, resulting in cellular states (Aim 1a), and characterize how somatic mutations dictate glioma lineage structure (Aim 1b). By combining this with my postdoctoral work – characterizing how epigenetic diversification contributes to transcriptomic diversity – I will create the first multi-dimensional model of glioma evolution. Second, I will use our method to measure single-cell DNA methylation and transcriptional profiles in samples taken longitudinally from the same patients. This will test the hypothesis that dysregulated epigenetic patterns contribute to glioma progression, and it will not only provide a multi-dimensional model of glioma progression, but will also provide epigenetic markers to track progression in the clinic (Aim 2). Finally, I will improve diagnosis in the clinical setting by designing a tool that infers cell state composition, progression and likely response to treatment based on data from the bulk DNA methylation assay that is routinely done in the clinic (Aim 3). These studies will pave the way towards novel glioma treatments, accurate diagnoses and optimal timing of treatment. Career Development Plan: I have outlined a 5-year career development plan to meet my goal of becoming an independent investigator in cancer biology who focuses on intrinsic determinants of tumor progression and response to treatment. I have assembled a Mentorship Committee of leaders in the field, with whom I will train to close remaining knowledge gaps in multi-omics evolution and how to leverage my results to support clinical care. Finally, the Broad Institute constitutes the ideal environment f... ## Key facts - **NIH application ID:** 10746909 - **Project number:** 4R00CA263149-03 - **Recipient organization:** UNIVERSITY OF PENNSYLVANIA - **Principal Investigator:** Dana Silverbush - **Activity code:** R00 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $249,000 - **Award type:** 4N - **Project period:** 2024-07-02 → 2027-06-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10746909 ## Citation > US National Institutes of Health, RePORTER application 10746909, Decoding glioma evolution and progression by multi-dimensional single-cell profiling (4R00CA263149-03). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10746909. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*